Abstract
The tasks of monitoring the state of complex technical objects are solved by evaluating and comparing experimental measurements. A new discrete analogue of the Smirnov-Cramer-von Mises criterion and a new discrete analogue of the Anderson criterion are proposed. Computational experiments have been carried out confirming the hypothesis that discrete models of the probability distribution function and the proposed discrete mean square of the difference in information content do not differ from the Anderson criterion and the Smirnov-Cramer-von Mises criterion, but it is much simpler in practical applications in the verification of statistical hypotheses homogeneity of short samples of experimental measurements.
Highlights
Computational experiments have been carried out confirming the hypothesis that discrete models of the probability distribution function and the proposed discrete mean square of the difference in information content do not differ from the Anderson criterion and the Smirnov-Cramer-von Mises criterion, but it is much simpler in practical applications in the verification of statistical hypotheses homogeneity of short samples of experimental measurements
Summary
Out confirming the hypothesis that discrete models of the probability distribution function and the proposed discrete mean square of the difference in information content do not differ from the Anderson criterion and the Smirnov-Cramer-von Mises criterion, but it is much simpler in practical applications in the verification of statistical hypotheses homogeneity of short samples of experimental measurements.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
